Vahagn: VisuAl Haptic Attention Gate Net for slip detection
To validate the effectiveness of method, we compared it with traditional CNN net and models with attention. It is anticipated that our method achieves a classification accuracy of 93.59%, which is higher than that of previous works. Attention visualization is further presented to support the validity.
Authors
- Yulong Ji (ORCID: https://orcid.org/0000-0001-7744-9306)
- Yang Hongyu
- Jinlin Wang (ORCID: https://orcid.org/0000-0003-1113-5835)
Institutions
- Sichuan University (CN)
Publication Details
- Journal
- Frontiers in Neurorobotics
- Published
- 2024-11-06
- DOI
- https://doi.org/10.3389/fnbot.2024.1484751
- Citations
- 2
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.69